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The same attributes were then used in Choice Experiments, but with completely revised communication arguments.
These attributes were then used to produce maps of the Pacific at a broad scale to establish the spatial diversity of the geologic and geomorphic attributes of the islands.
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These digital spatial document attributes are then used to retrieve and display a specific point or a selected region of the document.
Sampled values and correlated secondary attributes are then used in simple kriging with varying local means (SKLMs) to perform final mapping.
The attributes obtained were then used to conduct the second stage of study using path analysis.
The calibration dataset and covariates (i.e. pedological, geological and terrain attributes; land use; airborne gamma-ray spectrometry) were then used to build and extrapolate the decision tree using the C.5 algorithm in DSMART software.
We automatically extracted a multitude of topological attributes using Geographic Information Systems (GIS -like procedures that were then used in several combinations of feature selection schemes and probabilistic classification models to build and optimize classifiers for predictinGIS -likeels of the training sets.
The top attributes selected by the best-performing models were then used to build models with performance comparable to those using the entire dataset.
The hospital attributes selected by the respondent in the ACBC were then used to present the respondent with different hospitals.
The 'IN_FID' and 'NEAR_FID' fields (identifying the administrative unit of origin and destination, respectively) in the output 'distance' table were then used for joining twice the 'centroid attribute' table using the centroid 'ID' field to perform the join operation.
These values were then used to create an 11 by 11 matrix where the columns represented the score for the attribute.
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CEO of Professional Science Editing for Scientists @ prosciediting.com